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MAmmoTH2 8B Plus by TIGER-Lab

 »  All LLMs  »  TIGER-Lab  »  MAmmoTH2 8B Plus   URL Share it on

  14410   
  Arxiv:2405.03548   Autotrain compatible   Conversational Dataset:tiger-lab/webinstructs...   En   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TIGER-Lab/MAmmoTH2-8B-Plus 

MAmmoTH2 8B Plus Benchmarks

ARC: 62.29 vs 96.7 (so35)-35.6%
HellaSwag: 79.76 vs 95.3 (gpt4)-16.3%
MMLU: 64.3 vs 88.3 (so35)-27.2%
TruthfulQA: 54.59 vs 59 (gpt4)-7.5%
WinoGrande: 73.24 vs 87.5 (gpt4)-16.3%
GSM8K: 70.74 vs 96.4 (so35)-26.6%
LLME Score: 0.2749
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MAmmoTH2 8B Plus (TIGER-Lab/MAmmoTH2-8B-Plus)

MAmmoTH2 8B Plus Parameters and Internals

Model Type 
Language Model, Instruction Tuning
Use Cases 
Areas:
Research, Commercial applications
Applications:
Chatbots, Reasoning tasks
Limitations:
Performance may vary based on the complexity and specifics of the math problem., Not all mathematical fields can be covered comprehensively.
Supported Languages 
en (Proficient)
Training Details 
Data Sources:
https://huggingface.co/datasets/TIGER-Lab/WebInstructSub
Methodology:
The models are fine-tuned with the WEBINSTRUCT dataset using the original Llama-3, Mistral, and Mistal models as base models.
Input Output 
Accepted Modalities:
text
LLM NameMAmmoTH2 8B Plus
Repository 🤗https://huggingface.co/TIGER-Lab/MAmmoTH2-8B-Plus 
Model Size8b
Required VRAM16.1 GB
Updated2024-12-22
MaintainerTIGER-Lab
Model Typellama
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length8192
Model Max Length8192
Transformers Version4.40.0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|eot_id|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TIGER-Lab/MAmmoTH2-8B-Plus.

Rank the MAmmoTH2 8B Plus Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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